Devices for recognizing, identifying and validating objects such as coins are widely used in coin acceptor and coin rejecter mechanisms and many such devices are in existence and used on a regular basis. Such devices sense or feel the coin or other object as it moves past a sensing station and use this information in a device such as a microprocessor or the like to make a determination as to the genuineness, identity and validity of each coin. Such devices are very successful in accomplishing this. However, one of the problems encountered by such devices is the presence of variations in the same type of coin from batch to batch and over time and other variables including wear and dirt. These will cause changes, albeit small changes in some cases and from one coin type to another including in the U.S. and foreign coin markets. Such changes or variations can make it difficult if not impossible to distinguish between genuine and counterfeit coins or slugs where the similarities are relatively substantial compared to the differences.
The present invention takes a new direction in coin recognition, identification and validation by making use of a weighted error correlation coefficient algorithm. This technology has not been used heretofore in devices for sensing, identifying, recognizing and validating coins such as the coins fed into a vending or like machine. The use of weighted error correlation coefficient algorithm has the advantage over known devices by producing superior results when considering ease of implementation as opposed to more complex pattern recognition methods as it is a relatively transparent and straightforward algorithm, restriction to integer math due to being ultimately coded for a cost-effective embedded target, and ability to recognize data trends while still giving separation due to gross errors. The present invention therefore represents a technology in a coin sensing environment which has not been used in the past.